import { Algorithm } from "../types"

export const dynamicGraphAnalysis: Algorithm = {
  name: "动态异构图分析方法",
  description: "包含多种动态异构图的异常检测、链接预测、模式挖掘、演化预测等算法",
  configOptions: [
    {
      id: "analysisType",
      label: "分析类型",
      type: "select",
      options: [
        "异常检测",
        "链接预测",
        "模式挖掘",
        "演化预测",
        "社区发现",
        "影响力分析",
        "路径分析",
        "中心性分析",
        "相似性分析",
        "属性推断",
      ],
      defaultValue: "异常检测",
    },
    {
      id: "algorithm",
      label: "算法选择",
      type: "select",
      options: [
        "基于统计的方法",
        "基于深度学习的方法",
        "基于图神经网络的方法",
        "基于随机游走的方法",
        "基于矩阵分解的方法",
      ],
      defaultValue: "基于图神经网络的方法",
    },
    {
      id: "timeWindow",
      label: "时间窗口(小时)",
      type: "number",
      defaultValue: 24,
    },
    {
      id: "confidenceThreshold",
      label: "置信度阈值",
      type: "number",
      defaultValue: 0.75,
    },
    {
      id: "inputData",
      label: "输入数据路径",
      type: "text",
      defaultValue: "/data/dynamic_graph_sample.json",
    },
  ],
  execute: async (config) => {
    await new Promise((resolve) => setTimeout(resolve, 5000))

    const steps = [
      `初始化${config.analysisType}分析...`,
      `使用${config.algorithm}`,
      `加载数据: ${config.inputData}`,
      `设置时间窗口: ${config.timeWindow}小时`,
      `设置置信度阈值: ${config.confidenceThreshold}`,
      `预处理图数据...`,
      `提取时序特征...`,
      `构建分析模型...`,
      `训练/应用模型...`,
      `后处理结果...`,
      `生成可视化报告...`,
    ]

    let result = ""
    const accuracy = (Math.random() * 0.15 + 0.8).toFixed(4)
    const precision = (Math.random() * 0.15 + 0.8).toFixed(4)
    const recall = (Math.random() * 0.15 + 0.8).toFixed(4)
    const f1Score = (Math.random() * 0.15 + 0.8).toFixed(4)

    switch (config.analysisType) {
      case "异常检测":
        const anomalyCount = Math.floor(Math.random() * 50) + 10
        result = `检测到${anomalyCount}个异常节点/边
准确率: ${accuracy}
精确率: ${precision}
召回率: ${recall}
F1分数: ${f1Score}
主要异常类型: 突发连接、异常流量、结构变异`
        break
      case "链接预测":
        const predictedLinks = Math.floor(Math.random() * 1000) + 500
        result = `预测了${predictedLinks}个潜在链接
准确率: ${accuracy}
AUC: ${(Math.random() * 0.1 + 0.85).toFixed(4)}
Top-10准确率: ${(Math.random() * 0.1 + 0.9).toFixed(4)}`
        break
      case "模式挖掘":
        const patternCount = Math.floor(Math.random() * 20) + 5
        result = `发现了${patternCount}个显著模式
支持度: ${(Math.random() * 0.3 + 0.4).toFixed(4)}
置信度: ${(Math.random() * 0.2 + 0.7).toFixed(4)}
最大模式大小: ${Math.floor(Math.random() * 8) + 3}个节点`
        break
      case "演化预测":
        result = `成功预测未来${Math.floor(Math.random() * 5) + 1}个时间窗口的图演化
预测准确率: ${accuracy}
结构相似度: ${(Math.random() * 0.2 + 0.7).toFixed(4)}
趋势预测准确率: ${(Math.random() * 0.15 + 0.8).toFixed(4)}`
        break
      default:
        result = `分析完成，性能指标:
准确率: ${accuracy}
精确率: ${precision}
召回率: ${recall}
F1分数: ${f1Score}`
    }

    return {
      result,
      steps,
      executionTime: `${(Math.random() * 2000 + 4000).toFixed(2)}ms`,
    }
  },
} 